Analog radiation detectors, and in particular analog MCAs, have typically enabled users to record spectral data in time bins of not less than 1 second. This is often inadequate, however, for detection scenarios where a moving radioactive source is involved and the data acquisition window for collecting the majority data is a very short period of time. Especially at road speeds, such sources may come into “view” (i.e. high percentile detection range) only for a fraction of a second. For example, a radioactive source passing by at 65 mph with a closest approach to the detector of 3 meters, 80 percent of the radiation collected from the pass by will be collected in less than 0.5 seconds. Using 1 second time bins in these types of cases would average out many if not most features/events in the spectral data, and lose other details which would have otherwise provided valuable information as to the nature of the source and its movement. For example, signal fluctuations from the detector would not be easily scrutinizable for determining whether or not they are simply statistical fluctuations in the background or actual changes in the background due to a real radioactive source. Moreover, statistical fluctuations and non-uniform time bins due to MCA deficiencies can cause raggedness in the spectral data.
There is therefore a need for a fast MCA unit for use in a radiation detector (e.g. NaI detector), and capable of collecting and analyzing gamma radiation spectral data from a moving radioactive source in histogram mode, using very small time bins of preferably less than 1 millisecond, or list mode, or both, for high time resolution. In addition, it would be advantageous to provide a programmable MCA which may be specifically configured for various types of radiation detectors, and various operating parameters and detection modalities. Furthermore, it would also be advantageous to provide such a list mode MCA that is small, low power, self-contained, field-portable, field-programmable, and capable of providing real-time onboard data analysis.